The present invention relates to a weighting processing apparatus for digital signals and a weighting method thereof, and in particular to a digital signal weighting processing apparatus and a weighting method suitable for detecting weak signals in response to a measurement start signal of a medical appliance, an analyzer or the like.
If noise contained in a measured signal is white noise in case a weak signal is to be measured out of noise, noise can be reduced by taking the arithmetical mean value of these detected values.
Therefore, an arithmetical mean method whereby an arithmetical mean operation of sample values is conducted in synchronism with a measurement start signal to improve the signal-to-noise ratio is used for signal processing. Such an arithmetical mean method is described in "Digital Shingo Shori Nyumon" ("Introduction to digital Signal Processing", published in 1985 by Maruzen,) p. 93, for example. Assuming that, in such a prior method, sampling is performed at m points of time in each of a series of signal measurements performed n times, for example, these measurement results 1 to m are referred to as a measurement signal of a single time. In accordance with the prior art, a measurement comprising sampling 1 to m is repeated n times and the resultant m.times.n sample values undergo arithmetical mean processing.
In the case of a brain magnetic field measurement, for example, the above described arithmetical mean operation is conducted in synchronism with stimuli supplied to a living body. The resultant signal can be represented as EQU V.sub.j =1/n.multidot..SIGMA.V.sub.ij ( 1)
where .SIGMA. represents an addition performed n times.
In such a method to obtain the mean value in the prior art, sample values V.sub.1j to V.sub.nj at, say, the j-th sampling points based upon m sample signals contained in each of the measured signals resulting from measurements made n times in synchronism with the measurement start signal are added in an adder circuit and the resultant sum is divided by the number n of input signals, which is the number of times of measurement. If noise components contained in the measured signals are white noise. The noise components become relatively small by conducting the arithmetical mean operation. Signal detection by using the prior art method is thus made possible.
In case noise components contained in measured signals vary relatively largely for every measuring point and a large noise component is present in a certain specific measured signal as compared with signals at other measurement points of time, however, the result of the arithmetical mean operation is affected by this large noise component, resulting in a significantly lowered signal-to-noise ratio.